INTRODUCTION
Ultrasonographic anomalies and soft markers are common indications for
prenatal chromosomal analysis.1 Standard karyotyping
and chromosomal microarray (CMA) have become the primary diagnostic
tools for fetuses with growth disorders and congenital anomalies.
Recently, low-pass genome sequencing (low-pass GS) with enhanced
resolution and high throughput has emerged as an alternative to CMA for
genetic testing.2, 3 It has been applied to genetic
diagnoses in prenatal, miscarriage, and postnatal
cases,4-6 and was reported to have a 1.7%-3.4%
improvement in additional yield compared with routine
CMA.2, 6 Furthermore, low-pass GS has received
attention due to its shorter turnaround time, reduced DNA requirements,
lower technical repetition rate and lower cost.4
The yields of aneuploidy and likely pathogenic/pathogenic copy number
variations (pCNV) vary with different ultrasonographic findings.
Previous studies showed that the yield of pCNV was 6%-7% in
ultrasonography anomalous fetuses with a normal
karyotype,7, 8 and 0.4%-2% in fetuses without
anomalies.9-11 Cardiovascular, genitourinary,
skeletal, and central nervous system defects were reported to be most
commonly associated with chromosomal aberrations.12-18Therefore, the American College of Obstetricians and Gynecologists
(ACOG) and the Society for Maternal-Fetal Medicine (SMFM) recommend CMA
as a first-tier test in the diagnostic evaluation of fetal structural
abnormalities for fetuses undergoing prenatal
diagnosis.19 Additionally, previous studies have
demonstrated that aneuploidy and pCNV were frequently presented in
specific soft markers, such as increased nuchal translucency,
ventriculomegaly, and thickened nuchal fold.20-23 In
particular, the SMFM recommends CMA for fetuses with
ventriculomegaly.24 However, ultrasonographic
anomalies and soft markers comprise diverse subtypes, which may have
significant differences in the yield of aneuploidy and
pCNV.25-27
Therefore, it is crucial to systematically explore the correlation
between various ultrasonographic anomalies and soft markers and
aneuploidy/ pCNV. In this study, we comprehensively analyzed the yield
of aneuploidy and pCNV in 12 types of ultrasonographic anomalies and
soft markers based on a large cohort of 43,721 fetuses to provide data
support for the risk assessment of aneuploidy/pCNV underlying different
ultrasonographic findings. For each aneuploidy/pCNV, we compared the
ultrasonographic characteristics of fetuses with and without chromosomal
aberrations to elucidate the association of specific genomic alterations
with specific ultrasonographic anomalies.